Machine-learning method to find optimal solutions in extremely large design spaces

Electrical engineers at Duke University have devised a new method for solving difficult design problems with many potential solutions in a large design space using machine learning. Dubbed the "neural-adjoint method," the approach successfully unearths an optimized design for an electromagnetic communications device and could also be used for many other design challenges ranging from biomedical imaging to holography.